Molecular Neuroimaging of the Dopamine Transporter as a Patient Enrichment Biomarker for Clinical Trials for Early Parkinson's Disease

Empowering drug development: Leveraging insights from imaging technologies to enable the advancement of digital health technologies

The US Food and Drug Administration (FDA) has publicly recognized the importance of improving drug development efficiency, deeming translational biomarkers a top priority. The use of imaging biomarkers has been associated with increased rates of drug approvals. An appropriate level of validation provides a pragmatic way to choose and implement these biomarkers. Standardizing imaging modality selection, data acquisition protocols, and image analysis (in ways that are agnostic to equipment and algorithms) have been key to imaging biomarker deployment. The best known examples come from studies done via precompetitive collaboration efforts, which enable input from multiple stakeholders and data sharing. Digital health technologies (DHTs) provide an opportunity to measure meaningful aspects of patient health, including patient function, for extended periods of time outside of the hospital walls, with objective, sensor-based measures. We identified the areas where learnings from the imaging biomarker field can accelerate the adoption and widespread use of DHTs to develop novel treatments. As with imaging, technical validation parameters and performance acceptance thresholds need to be established. Approaches amenable to multiple hardware options and data processing algorithms can be enabled by sharing DHT data and by cross-validating algorithms. Data standardization and creation of shared databases will be vital. Pre-competitive consortia (public-private partnerships and professional societies that bring together all stakeholders, including patient organizations, industry, academic experts, and regulators) will advance the regulatory maturity of DHTs in clinical trials.

Leveraging the regulatory framework to facilitate drug development in Parkinson's disease

There is an exigent need for disease-modifying and symptomatic treatment approaches for Parkinson's disease. A better understanding of Parkinson's disease pathophysiology and new insights in genetics has opened exciting new venues for pharmacological treatment targets. There are, however, many challenges on the path from discovery to drug approval. These challenges revolve around appropriate endpoint selection, the lack of accurate biomarkers, challenges with diagnostic accuracy, and other challenges commonly encountered by drug developers. The regulatory health authorities, however, have provided tools to provide guidance for drug development and to assist with these challenges. The main goal of the Critical Path for Parkinson's Consortium, a nonprofit public-private partnership part of the Critical Path Institute, is to advance these so-called drug development tools for Parkinson's disease trials. The focus of this chapter will be on how the health regulators' tools were successfully leveraged to facilitate drug development in Parkinson's disease and other neurodegenerative diseases.

Pharmacometrics: The Already-Present Future of Precision Pharmacology

The use of mathematical modeling to represent, analyze, make predictions or providing information on data obtained in drug research and development has made pharmacometrics an area of great prominence and importance. The main purpose of pharmacometrics is to provide information relevant to the search for efficacy and safety improvements in pharmacotherapy. Regulatory agencies have adopted pharmacometrics analysis to justify their regulatory decisions, making those decisions more efficient. Demand for specialists trained in the field is therefore growing. In this review, we describe the meaning, history, and development of pharmacometrics, analyzing the challenges faced in the training of professionals. Examples of applications in current use, perspectives for the future, and the importance of pharmacometrics for the development and growth of precision pharmacology are also presented.

Innovations in Therapy Development for Rare Diseases Through the Rare Disease Cures Accelerator-Data and Analytics Platform

Rare diseases impact the lives of an estimated 350 million people worldwide, and yet about 90% of rare diseases remain without an approved treatment. New technologies have become available, such as gene and oligonucleotide therapies, that offer great promise in treating rare diseases. However, progress toward the development of therapies to treat these diseases is hampered by a limited understanding of the course of each rare disease, how changes in disease progression occur and can be effectively measured over time, and challenges in designing and running clinical trials in diseases where the natural history is poorly characterized. Data that could be used to characterize the natural history of each disease has often been collected in various ways, including in electronic health records, patient-report registries, clinical natural history studies, and in past clinical trials. However, each data source contains a limited number of subjects and different data elements, and data is frequently kept proprietary in the hands of the study sponsor rather than shared widely across the rare disease community. The Rare Disease Cures Accelerator-Data and Analytics Platform (RDCA-DAP) is an FDA-funded effort to overcome these persistent challenges. By aggregating data across all rare diseases and making that data available to the community to support understanding of rare disease natural history and inform drug development, RDCA-DAP aims to accelerate the regulatory approval of new therapies. RDCA-DAP curates, standardizes, and tags data across rare disease datasets to make it findable within the database, and contains a built-in analytics platform to help visualize, interpret, and use it to support drug development. RDCA-DAP will coordinate data and tool resources across non-profit, commercial, and for-profit entities to serve a diverse array of rare disease stakeholders that includes academic researchers, drug developers, FDA reviewers and of course patients and their caregivers. Drug development programs utilizing the RDCA-DAP will be able to leverage existing data to support their efforts and reach definitive decisions on the efficacy of their therapeutics more efficiently and more rapidly than ever.

Biomarkers in Medicines Development-From Discovery to Regulatory Qualification and Beyond

Biomarkers are important tools in medicines development and clinical practice. Besides their use in clinical trials, such as for enrichment of patients, monitoring safety or response to treatment, biomarkers are a cornerstone of precision medicine. The European Medicines Agency (EMA) emphasised the importance of the discovery, qualification, and use of biomarkers in their Regulatory Science Strategy to 2025, which included the recommendation to enhance early engagement with biomarker developers to facilitate regulatory qualification. This study explores the journey of biomarkers through the EU regulatory system and beyond, based on a review of interactions between developers and the EMA from 2008 to 2020, as well as the use of qualified biomarkers in clinical trials. Of applicants that used early interaction platforms such as the Innovation Task Force, less than half engaged in fee-related follow-up procedures. Results showed that, as compared to companies, consortia were more likely to opt for the Qualification of Novel Methodologies procedure and engage in follow-up procedures. Our results highlight the importance of early engagement with regulators for achieving biomarker qualification, including pre-submission discussions in the context of the qualification procedure. A review of clinical trials showed that all qualified biomarkers are used in practice, although not always according to the endorsed context of use. Overall, this study highlights important aspects of biomarker qualification, including opportunities to improve the seamless support for developers by EMA. The use of qualified biomarkers in clinical trials underlines the importance of regulatory qualification, which will further enable precision medicine for the benefit of patients.

Role of Brain Imaging in Drug Development for Psychiatry

Background:

Over the last decades, many brain imaging studies have contributed to new insights in the pathogenesis of psychiatric disease. However, in spite of these developments, progress in the development of novel therapeutic drugs for prevalent psychiatric health conditions has been limited.

Objective:

In this review, we discuss translational, diagnostic and methodological issues that have hampered drug development in CNS disorders with a particular focus on psychiatry. The role of preclinical models is critically reviewed and opportunities for brain imaging in early stages of drug development using PET and fMRI are discussed. The role of PET and fMRI in drug development is reviewed emphasizing the need to engage in collaborations between industry, academia and phase I units.

Conclusion:

Brain imaging technology has revolutionized the study of psychiatric illnesses, and during the last decade, neuroimaging has provided valuable insights at different levels of analysis and brain organization, such as effective connectivity (anatomical), functional connectivity patterns and neurochemical information that may support both preclinical and clinical drug development. Since there is no unifying pathophysiological theory of individual psychiatric syndromes and since many symptoms cut across diagnostic boundaries, a new theoretical framework has been proposed that may help in defining new targets for treatment and thus enhance drug development in CNS diseases. In addition, it is argued that new proposals for data-mining and mathematical modelling as well as freely available databanks for neural network and neurochemical models of rodents combined with revised psychiatric classification will lead to new validated targets for drug development.

Dopamine Transporter Imaging, Current Status of a Potential Biomarker: A Comprehensive Review

A major goal of current clinical research in Parkinson's disease (PD) is the validation and standardization of biomarkers enabling early diagnosis, predicting outcomes, understanding PD pathophysiology, and demonstrating target engagement in clinical trials. Molecular imaging with specific dopamine-related tracers offers a practical indirect imaging biomarker of PD, serving as a powerful tool to assess the status of presynaptic nigrostriatal terminals. In this review we provide an update on the dopamine transporter (DAT) imaging in PD and translate recent findings to potentially valuable clinical practice applications. The role of DAT imaging as diagnostic, preclinical and predictive biomarker is discussed, especially in view of recent evidence questioning the incontrovertible correlation between striatal DAT binding and nigral cell or axon counts.

Effect of Urate-Elevating Inosine on Early Parkinson Disease Progression: The SURE-PD3 Randomized Clinical Trial

Importance

Urate elevation, despite associations with crystallopathic, cardiovascular, and metabolic disorders, has been pursued as a potential disease-modifying strategy for Parkinson disease (PD) based on convergent biological, epidemiological, and clinical data.

Objective

To determine whether sustained urate-elevating treatment with the urate precursor inosine slows early PD progression.

Design, Participants, and Setting

Randomized, double-blind, placebo-controlled, phase 3 trial of oral inosine treatment in early PD. A total of 587 individuals consented, and 298 with PD not yet requiring dopaminergic medication, striatal dopamine transporter deficiency, and serum urate below the population median concentration (<5.8 mg/dL) were randomized between August 2016 and December 2017 at 58 US sites, and were followed up through June 2019.

Interventions

Inosine, dosed by blinded titration to increase serum urate concentrations to 7.1-8.0 mg/dL (n = 149) or matching placebo (n = 149) for up to 2 years.

Main Outcomes and Measures

The primary outcome was rate of change in the Movement Disorder Society Unified Parkinson Disease Rating Scale (MDS-UPDRS; parts I-III) total score (range, 0-236; higher scores indicate greater disability; minimum clinically important difference of 6.3 points) prior to dopaminergic drug therapy initiation. Secondary outcomes included serum urate to measure target engagement, adverse events to measure safety, and 29 efficacy measures of disability, quality of life, cognition, mood, autonomic function, and striatal dopamine transporter binding as a biomarker of neuronal integrity.

Results

Based on a prespecified interim futility analysis, the study closed early, with 273 (92%) of the randomized participants (49% women; mean age, 63 years) completing the study. Clinical progression rates were not significantly different between participants randomized to inosine (MDS-UPDRS score, 11.1 [95% CI, 9.7-12.6] points per year) and placebo (MDS-UPDRS score, 9.9 [95% CI, 8.4-11.3] points per year; difference, 1.26 [95% CI, -0.59 to 3.11] points per year; P = .18). Sustained elevation of serum urate by 2.03 mg/dL (from a baseline level of 4.6 mg/dL; 44% increase) occurred in the inosine group vs a 0.01-mg/dL change in serum urate in the placebo group (difference, 2.02 mg/dL [95% CI, 1.85-2.19 mg/dL]; P<.001). There were no significant differences for secondary efficacy outcomes including dopamine transporter binding loss. Participants randomized to inosine, compared with placebo, experienced fewer serious adverse events (7.4 vs 13.1 per 100 patient-years) but more kidney stones (7.0 vs 1.4 stones per 100 patient-years).

Conclusions and Relevance

Among patients recently diagnosed as having PD, treatment with inosine, compared with placebo, did not result in a significant difference in the rate of clinical disease progression. The findings do not support the use of inosine as a treatment for early PD.

Trial Registration

ClinicalTrials.gov Identifier: NCT02642393.

The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

Imaging biomarkers play a wide-ranging role in clinical trials for neurological disorders. This includes selecting the appropriate trial participants, establishing target engagement and mechanism-related pharmacodynamic effect, monitoring safety, and providing evidence of disease modification. In the early stages of clinical drug development, evidence of target engagement and/or downstream pharmacodynamic effect-especially with a clear relationship to dose-can provide confidence that the therapeutic candidate should be advanced to larger and more expensive trials, and can inform the selection of the dose(s) to be further tested, i.e., to "de-risk" the drug development program. In these later-phase trials, evidence that the therapeutic candidate is altering disease-related biomarkers can provide important evidence that the clinical benefit of the compound (if observed) is grounded in meaningful biological changes. The interpretation of disease-related imaging markers, and comparability across different trials and imaging tools, is greatly improved when standardized outcome measures are defined. This standardization should not impinge on scientific advances in the imaging tools per se but provides a common language in which the results generated by these tools are expressed. PET markers of pathological protein aggregates and structural imaging of brain atrophy are common disease-related elements across many neurological disorders. However, PET tracers for pathologies beyond amyloid β and tau are needed, and the interpretability of structural imaging can be enhanced by some simple considerations to guard against the possible confound of pseudo-atrophy. Learnings from much-studied conditions such as Alzheimer's disease and multiple sclerosis will be beneficial as the field embraces rarer diseases.

Emerging Targeted Therapeutics for Genetic Subtypes of Parkinsonism

In recent years, a precision medicine approach, which customizes medical treatments based on patients' individual profiles and incorporates variability in genes, the environment, and lifestyle, has transformed medical care in numerous medical fields, most notably oncology. Applying a similar approach to Parkinson's disease (PD) may promote the development of disease-modifying agents that could help slow progression or possibly even avert disease development in a subset of at-risk individuals. The urgent need for such trials partially stems from the negative results of clinical trials where interventions treat all PD patients as a single homogenous group. Here, we review the current obstacles towards the development of precision interventions in PD. We also review and discuss the clinical trials that target genetic forms of PD, i.e., GBA-associated and LRRK2-associated PD.

A disease progression model of longitudinal lung function decline in idiopathic pulmonary fibrosis patients

Pirfenidone and nintedanib are the first two FDA-approved therapies for treatment of idiopathic pulmonary fibrosis (IPF). The clinical programs for pirfenidone and nintedanib included 1132 patients in the placebo arms and 1691 patients in the treatment arms across 6 trials. We developed a disease progression model to characterize the observed variability in lung function decline, measured as percent predicted forced vital capacity (%p-FVC), and its decrease in decline after treatment. The non-linear longitudinal change in %p-FVC was best described by a Weibull function. The median decreased decline in %p-FVC after treatment was estimated to be 1.50% (95% CI [1.12, 1.79]) and 1.96% (95% CI [1.47, 2.36]) at week 26 and week 52, respectively. Smoking status, weight, %p-FVC, %p-DLco and oxygen use at baseline were identified as significant covariates affecting decline in %p-FVC. The decreased decline in %p-FVC were observed among all subgroups of interest, of which the effects were larger at 1 year compared to 6 months. Based on the disease progression model smoking status and oxygen use at baseline may affect the treatment effect size. At week 52, the decreased decline in %p-FVC for current smokers and patients with oxygen use at baseline were 1.56 (90% CI [1.02, 1.99]) and 2.32 (90% CI [1.74, 2.86]), respectively. These prognostic factors may be used to enrich studies with patients who are more likely to respond to treatment, by demonstrating a lesser decline in lung function, and therefore provide the potential to allow for IPF studies with smaller study populations or shorter durations.

Open Data Revolution in Clinical Research: Opportunities and Challenges

Efforts for sharing individual clinical data are gaining momentum due to a heightened recognition that integrated data sets can catalyze biomedical discoveries and drug development. Among the benefits are the fact that data sharing can help generate and investigate new research hypothesis beyond those explored in the original study. Despite several accomplishments establishing public systems and guidance for data sharing in clinical trials, this practice is not the norm. Among the reasons are ethical challenges, such as privacy of individuals, data ownership, and control. This paper creates awareness of the potential benefits and challenges of sharing individual clinical data, how to overcome these challenges, and how as a clinical pharmacology community we can shape future directions in this field.

Hippocampal Neuroimaging-Informed Clinical Trial Enrichment Tool for Amnestic Mild Cognitive Impairment Using Open Data

Our goal was to assess the enrichment utility of hippocampal volume (HV) as an enrichment biomarker in amnestic mild cognitive impairment (aMCI) clinical trials, and, hence, develop an HV neuroimaging-informed clinical trial enrichment tool. Modeling of integrated longitudinal patient-level data came from open-access natural history studies in patients diagnosed with aMCI-the Alzheimer's Disease Neuroimaging Initiative (ADNI)-1 and ADNI-2-and indicated that a decrease of 1 cm³ with respect to the analysis dataset median baseline intracranial volume-adjusted HV (ICV-HV; ~ 5 cm³ ) is associated with > 50% increase in disease progression rate as measured by the Clinical Dementia Rating Scale-Sum of Boxes. Clinical trial simulations showed that the inclusion of aMCI subjects with baseline ICV-HV below the 84th or 50th percentile allowed an approximate reduction in trial size of at least 26% and 55%, respectively. This clinical trial enrichment tool can help design more efficient and informative clinical trials.

Innovative Approaches for Slowing Disease Progression in Parkinson's Disease: Takeaways from the 14th Annual International Society for Central Nervous System Clinical Trials and Methodology Scientific Meeting

The International Society for Central Nervous System Clinical Trials and Methodology (ISCTM) partnered with the Michael J. Fox Foundation for Parkinson's Research to hold a joint session on innovation in Parkinson's disease research at the ISCTM 14th Annual Scientific Meeting held February 20 to 22, 2018 in Washington, D.C. The session focused on (1) biomarkers and outcomes measures in Parkinson's disease clinical trials; 2) clinical trial designs, outcomes, and statistical approaches; and 3) the path forward. This paper aims to summarize key takeaways from the session presenters, panelists, and audience members.

The Qualification of an Enrichment Biomarker for Clinical Trials Targeting Early Stages of Parkinson's Disease

As therapeutic trials target early stages of Parkinson's disease (PD), appropriate patient selection based purely on clinical criteria poses significant challenges. Members of the Critical Path for Parkinson's Consortium formally submitted documentation to the European Medicines Agency (EMA) supporting the use of Dopamine Transporter (DAT) neuroimaging in early PD. Regulatory documents included a comprehensive literature review, a proposed analysis plan of both observational and clinical trial data, and an assessment of biomarker reproducibility and reliability. The research plan included longitudinal analysis of the Parkinson Research Examination of CEP-1347 Trial (PRECEPT) and the Parkinson's Progression Markers Initiative (PPMI) study to estimate the degree of enrichment achieved and impact on future trials in subjects with early motor PD. The presence of reduced striatal DAT binding based on visual reads of single photon emission tomography (SPECT) scans in early motor PD subjects was an independent predictor of faster decline in UPDRS Parts II and III as compared to subjects with scans without evidence of dopaminergic deficit (SWEDD) over 24 months. The EMA issued in 2018 a full Qualification Opinion for the use of DAT as an enrichment biomarker in PD trials targeting subjects with early motor symptoms. Exclusion of SWEDD subjects in future clinical trials targeting early motor PD subjects aims to enrich clinical trial populations with idiopathic PD patients, improve statistical power, and exclude subjects who are unlikely to progress clinically from being exposed to novel test therapeutics.